On perturbed steepest descent methods with inexact line search for bilevel convex optimization
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Publication:3112499
DOI10.1080/02331934.2010.536231zbMath1233.90233OpenAlexW2047859246MaRDI QIDQ3112499
Elias Salomão Helou Neto, Alvaro Rodolfo de Pierro
Publication date: 10 January 2012
Published in: Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331934.2010.536231
Related Items (6)
Alternated and multi-step inertial approximation methods for solving convex bilevel optimization problems ⋮ A primal nonsmooth reformulation for bilevel optimization problems ⋮ Derivative-free superiorization with component-wise perturbations ⋮ Projected subgradient minimization versus superiorization ⋮ A First Order Method for Solving Convex Bilevel Optimization Problems ⋮ String-averaging projected subgradient methods for constrained minimization
Cites Work
- Unnamed Item
- Nonlinear total variation based noise removal algorithms
- A simultaneous projections method for linear inequalities
- A relaxed version of Bregman's method for convex programming
- Incremental gradient algorithms with stepsizes bounded away from zero
- Error stability properties of generalized gradient-type algorithms
- Two facts on the convergence of the Cauchy algorithm
- An overview of bilevel optimization
- Mathematical Methods in Image Reconstruction
- Incremental Subgradient Methods for Nondifferentiable Optimization
- Convergence results for scaled gradient algorithms in positron emission tomography
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Decoding by Linear Programming
- Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
- From convex feasibility to convex constrained optimization using block action projection methods and underrelaxation
- Incremental Subgradients for Constrained Convex Optimization: A Unified Framework and New Methods
- A Simultaneous Iterative Method for Computing Projections on Polyhedra
- Signal Recovery and the Large Sieve
- A New Class of Incremental Gradient Methods for Least Squares Problems
- An Incremental Gradient(-Projection) Method with Momentum Term and Adaptive Stepsize Rule
- Gradient Convergence in Gradient methods with Errors
- Convergence of Approximate and Incremental Subgradient Methods for Convex Optimization
- Full convergence of the steepest descent method with inexact line searches
- A Statistical Model for Positron Emission Tomography
- A Convergent Incremental Gradient Method with a Constant Step Size
- For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solution
- For most large underdetermined systems of equations, the minimal 𝓁1‐norm near‐solution approximates the sparsest near‐solution
- Stable signal recovery from incomplete and inaccurate measurements
- Compressed sensing
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